Systems and methods for automated authoring, distributing, and processing electronic data files

ABSTRACT

A computerized enhanced discreet coupon (EDC) processing system processes shopper EDC(s) using a scanner and a processor. The scanner scans purchased items. The processor generates tickets corresponding to the purchased items, syntactically validates shopper EDC(s), semantically checks the EDC(s), and authenticates the EDC(s). If an EDC is authentic, then the processor compares the EDC against the ticket to determine if the EDC qualifies, and if so, then the EDC is redeemable. Authentication can be accomplished by, for example, comparing EDC rule(s) and/or rule identifier(s) against genuine rule/identifier sets. Genuine rule set includes a qualifying rule and a redemption rule.

This application claims priority to U.S. Provisional Application Ser.No. 61/557,437 filed on Nov. 9, 2011, entitled “Coupon DefinitionSystem”, which is incorporated by reference herein for all purposes.

BACKGROUND

The present invention generally relates to improving the discountingfunctionality and security of point-of-sale (POS) processing systems,and more particularly relates to authoring, distributing POS processing,and post-processing of substantially improved discount coupons.

Conventional legacy discount coupons have been standardized and inwidespread use at many retail stores for many years. Legacy couponsinclude only two fields, a product category field and a discount typefield, each field being 256-bits in length.

The very limited number of fields and limited field length necessitatesthe use of broad product categories and also results in a limited numberof discount types. As a result, these legacy discount coupons are veryinflexible and also very susceptible to fraud. For example, anunscrupulous shopper may attempt to present a “$5 discount” coupon,intended for an item retailing for $50, towards the purchase of asignificantly lower priced item retailing for $3, assuming that the $3item is in the same product category as the $50 item. If the salesassociate at the point of sale (POS) is not alert and the number ofitems purchased by the shopper is large enough, then the shopper ends upwith a $2 net cash credit towards the purchase of the other items ($3item minus $5 discount). In other words, the shopper was rewarded a $2cash credit for merely acquiring the $3 item at no cost.

Hence there is an urgent need for an improved automated POS systemcapable of processing a wider variety of discounts for a wider varietyof products and product categories, while substantially decreasingfraud.

SUMMARY

To achieve the foregoing and in accordance with the present invention,systems and methods for authoring, distributing, point-of-sale (POS)processing, and post-processing of Enhanced Discrete Coupon(s) (EDC) areprovided. In particular, the systems and methods provide a facility toenable and encourage shoppers to identify and seek out goods and/orservices that may be acquired at special incentivizing prices, providedthat for a given EDC, certain conditions set by the EDC issuer andencoded in the EDC are satisfied.

In one embodiment, a computerized enhanced discreet coupon (EDC)processing system is configured to process at least one enhanceddiscrete coupon (EDC) presented by a shopper. The EDC processing systemincludes a scanner and an EDC processor. The scanner is configured toscan one or more purchase items selected by a shopper. The EDC processoris configured to generate a ticket corresponding to the at least onepurchase item, to syntactically validate at least one enhanced discretecoupon (EDC) presented by the shopper, to semantically check the atleast one EDC, and to authenticate the at least one EDC. If the EDC isdetermined to be authentic, then the EDC processor compares the at leastone EDC against the ticket to determine if the EDC qualifies, and if theEDC is both authentic and qualifies, then the EDC is permitted to beredeemed by the shopper.

In some embodiments, the EDC includes at least two EDC rule identifiers,and the authenticating includes comparing the at least two EDC ruleidentifiers with a plurality of genuine rule identifier sets associatedwith a corresponding plurality of genuine rule sets, wherein eachgenuine rule set includes a qualifying rule and a redemption rule. Inanother embodiment, the EDC includes an EDC rule set, and theauthenticating includes comparing the EDC rule set with a plurality ofgenuine rule sets, wherein each genuine rule set includes a qualifyingrule and a redemption rule. In yet another embodiment, the EDC includesan EDC rule and an EDC rule identifier, and the authenticating includescomparing the EDC rule and the EDC rule identifier with a plurality ofgenuine rule and rule identifier sets, wherein each genuine rule andrule identifier set includes a qualifying rule associated with aredemption rule identifier or a qualifying rule identifier associatedwith a redemption rule.

Depending on the implementation, the qualifying rules and the redemptionrules can either be static or variable, and the EDC can include one ormore rule operands associated with any variable rule(s). Qualifyingand/or redemption rules can either be simple or compound.

The EDC can include one or more additional fields. Exemplary additionalEDC field(s) may include inception date, duration, expiration date,and/or shopper identifier. The additional EDC field(s) can also beextendable.

Note that the various features of the present invention described abovemay be practiced alone or in combination. These and other features ofthe present invention will be described in more detail below in thedetailed description of the invention and in conjunction with thefollowing figures.

BRIEF DESCRIPTION OF THE DRAWINGS

In order that the present invention may be more clearly ascertained,some embodiments will now be described, by way of example, withreference to the accompanying drawings, in which:

FIG. 1 is a System Level Block Diagram of a POS Enhanced Discrete Coupon(EDC) Processing System in accordance with an embodiment of the presentinvention;

FIG. 2 is a Top Level Logic Flow Diagram in accordance with a POS EDCProcessing System embodiment;

FIG. 3 is an exemplary screen shot of an EDC authoring facility inaccordance with a POS EDC Processing System embodiment;

FIG. 4 is a Diagram of EDC fields in accordance with a POS EDCProcessing System embodiment;

FIG. 5 is a Logic Flow Diagram that further decomposes Step 260 of FIG.2 so as to describe the POS processing of EDC(s) in accordance with aPOS EDC Processing System embodiment;

FIG. 6 is a Logic Flow Diagram that further decomposes Step 530 of FIG.5 so as to describe the parsing and syntactical validation of an EDC inaccordance with a POS EDC Processing System embodiment;

FIG. 7 is a Logic Flow Diagram that further decomposes Step 540 of FIG.5 so as to describe the semantical checking and authentication of an EDCin accordance with a POS EDC Processing System embodiment; and

FIG. 8 is a Logic Flow Diagram that further decomposes Step 550 of FIG.5 so as to describe the comparison of an EDC against the ticket and theredemption of an EDC in accordance with a POS EDC Processing Systemembodiment.

DETAILED DESCRIPTION

The present invention will now be described in detail with reference toseveral embodiments thereof as illustrated in the accompanying drawings.In the following description, numerous specific details are set forth inorder to provide a thorough understanding of embodiments of the presentinvention. It will be apparent, however, to one skilled in the art, thatembodiments may be practiced without some or all of these specificdetails. In other instances, well known process steps and/or structureshave not been described in detail in order to not unnecessarily obscurethe present invention. The features and advantages of embodiments may bebetter understood with reference to the drawings and discussions thatfollow.

The present invention relates generally to systems and methods forauthoring, distributing, point-of-sale (POS) processing, andpost-processing of Enhanced Discrete Coupon(s) (EDC). In particular, thepresent invention—the Point-of-Sale Enhanced Discrete Coupon ProcessingSystem—is directed to novel methods and systems to provide goodsmanufacturers, service providers, goods and/or service sellers, andaffiliated third party marketers (“EDC issuers”) a facility to enableand encourage savings-motivated consumers (“shoppers”) to become awareof and seek out goods and/or services that may be acquired at specialincentivizing prices and to purchase said goods and/or servicesaccordingly—provided that for a given EDC, certain conditions set by theEDC issuer and encoded in the EDC are satisfied. For example, anincentivizing price may be a discounted price for a specified purchaseitem, or for a specified group of purchase items, or for specifiedpurchase item(s) conditioned on the purchase of certain other specifieditem(s).

To facilitate discussion, FIG. 1 shows an exemplary structural blockdiagram of the Point-of-Sale (POS) Enhanced Discrete Coupon (EDC)Processing System. Such a POS EDC Processing System 150 may includecertain system components located at the point-of-sale such as POS InputDevice(s) 152, POS Display Device(s) 154, POS Processor 155—which mayinclude an EDC Interpreter 155 a, and EDC Depository 157. A POS EDCProcessing System 150 may be securely and reliably coupled via Wide AreaNetwork 160 with EDC Server(s) 170 with Remote EDC Depository 175. EDCServer(s) 170 may be centrally located or distributed; and maypotentially employ redundancy, mirroring and load-balancing, in additionto other techniques known to one skilled in the art, to increase thesustained and burst rate processing capacity and fault tolerance of EDCServer(s) 170. In some embodiments, one or more POS EDC ProcessingSystem(s) 150 may be coupled to a given EDC Server(s) 170.

In some embodiments, at the POS there may be one or more POS InputDevice(s) 152 and one or more POS Display Device(s) 154 configuredtogether with a POS Processor 155 including EDC Interpreter 155 a, andan EDC Depository 157—composing an POS EDC Processing System 150—so asto allow shopper(s) 110 to have purchase items (not shown) scanned aswell as EDC(s) 115 received, so as EDC(s) may be qualified, and ifaccepted, redeemed by said POS EDC Processing System 150. Saidcomponents of System 150 may interconnect in one or more combinationsand/or configurations—e.g., utilizing cable(s), bus(es) and/or localarea network(s).

Utilizing the POS Input Device(s) 152 configured to scan purchaseitem(s)—each purchase item selected by shopper 110 may be scanned,identified, counted and priced by the POS Processor 155; and suchinformation may be recorded so as to generate a corresponding quantifiedlist, i.e., the “ticket”. In addition, the ticket may record anydiscount(s) specified by redeemed EDC(s) as well as the net payment duefrom the shopper 110 to compensate the seller (not shown) for thepurchase item(s). The ticket may also include the processing date of theticket—the “POS transaction date”. Furthermore, the ticket may includetransaction details such as: identification of the seller, method ofpayment, and if available, information identifying the shopper 110.Information from the ticket may be used subsequently to composereceipt(s).

In addition to scanning purchase item(s), the POS Input Device(s) 152may be utilized to receive EDC(s) 115 which the EDC Interpreter 155 amay store in the EDC Depository 157. Additional information stored inthe EDC Depository 157 may include ticket information and also entriesrecorded in a transaction log (not shown). Transaction log entries mayrecord information from the POS processing of EDC(s) as well asinformation related to facilitating POS EDC processing. Forexample—subsequent to completing updates to the EDC Interpreter 155a—status, diagnostic and completion entries to the transaction log maybe stored in the EDC Depository 157.

The POS EDC Processing System 150 may facilitate utilizations of EDC(s)by EDC issuers, by sellers, and by shoppers 110. In some embodiments—asillustrated in FIG. 2 —the POS EDC Processing System 150 may supportand/or utilize the following facilities: authoring of EDC(s), updatingof POS EDC Processing Systems, distributing EDC(s), processing of EDC(s)at the POS, and post-processing of EDC(s).

Referring to step 220, EDC(s) 115 may be authored utilizing one or moredevices (not shown) including, but not limited to, personal computers,laptop computers, tablet computers, “smart phones”, and almost anyelectronic computing device that includes network access and a graphicaluser interface.

FIG. 3 shows an exemplary EDC authoring screenshot 300 for an EDCauthoring facility (not shown) for authoring any given EDC 115.

In some embodiments, referring to FIG. 4 , a given utilization of an EDCauthoring facility may result in authored EDC(s) stored in a Remote EDCDepository 175. An EDC 115 may include one or more fields—such as: EDCRule Field 401 and optionally EDC Additional Field(s) 402. EDC RuleField 401 includes EDC rule(s) and/or EDC rule identifier(s). An EDCrule may be a “qualification rule” and/or a “redemption rule”.

A qualification rule specifies to the EDC Interpreter 155 a action(s)required of the shopper 110 and detected at the POS by the System 150 soas an EDC 115—which includes said rule—qualifies for acceptance so as tobe redeemed by the System 150. For example, a qualification rule mayrequire that a specific quantity of a specific purchase item be selectedby the shopper 110 and scanned by the System 150 and listed in thecorresponding ticket—i.e., ‘purchase quantity 4 of purchase item Mumby'sYumby Brand 32 oz Instant Chai Tea’.

A redemption rule specifies to the EDC Interpreter 155 a action(s)required of the System 150 to redeem a received EDC 115. For example, aredemption rule may require that a discount be applied to a purchaseitem(s) identified in the ticket—i.e., ‘discount an amount Y offpurchase price of purchase item Z’. Further by example, a redemptionrule may specify ‘discount $1.14 off the purchase price of Kidd's PrufBrand 16 oz Insulated Tea Mug’. Redemption rules may vary widely, butcommonly they specify a credit(s)—such as a discount(s) and/or arebate(s)—effecting a decrease(s) in the net payment recorded in theticket and due of the shopper 110.

In some embodiments, an EDC rule may include more than onerule—typically with each rule combined with the other rule(s) using forexample boolean operators(s) such as ‘and’ and/or ‘or’—so as to form a“compound” rule. For example, a compound qualification rule may specify:‘purchase quantity 4 of purchase item Mumby's Yumby Brand 16 ozVitalmineral H2Oh!—or—purchase quantity 2 of Kidd's Pruf Brand FlexzableSlurping Straws’. Similarly for example, a compound redemption rule mayspecify: ‘discount $2.00 off of entire ticket—and—credit 200 points toshopper's loyalty account’. A common example of a compound qualifyingrule is a requirement(s) for specified purchase item(s) andcorresponding quantity(s) coupled with a rule specifying the EDC may beredeemed no later than a specific “expiration date”. Some EDC(s) mayinclude rules that do not specify an expiration date which in someembodiments may imply that the EDC may not expire. Some EDC(s) mayinclude a rule and/or operand field that explicitly specifies: ‘noexpiration date’.

In some embodiments, an EDC rule may be a “variable” rule in that itincludes a numerical amount or other specifier—such as where saidspecifier may be represented indirectly by a variable and further wherethe value corresponding to that variable is included in a separatecorresponding “operand” field. So for example, a variable qualificationrule may specify: ‘purchase quantity [variable X] of Kidd's Pruf Brand30 count Wunder Wypes’ where the operand field specifying variable X mayinclude the value ‘3’. Furthermore, a variable rule may utilize morethan one operand fields; so for example, a variable redemption rulemight specify: ‘discount off entire ticket quantity [variable Y] ofdenomination [variable Z]’ where the operand field specifying variable Ymay include the value ‘5’ and the operand field specifying variable Zmay include the value ‘dollars’. Such a variable rule would be thesemantic equivalent of a “static” rule that specifies: ‘discount offentire ticket quantity 5 of denomination dollars’.

Operand fields may be stored in the Additional EDC Field(s) 402 of anEDC. In some embodiments, the variable values corresponding to avariable rule may be included in an operand field or operand field(s) inthe form of an n-tuple. For example, the variable redemption rule in theprevious example may utilize a 2-tuple to specify the discount quantityand the corresponding discount denomination, i.e., ‘5’:‘dollars’. Ann-tuple may be stored in an EDC field or more than one EDC field(s). Anexample of a common 2-tuple is: a purchase item identifier—such as astock-keeping unit code (SKU)—and corresponding item quantity. Asmentioned previously, another 2-tuple may be: discount amount andcorresponding discount denomination where the denomination might forexample be ‘dollars’ or ‘pesos’ or ‘percent’ or ‘loyalty points’.Another 2-tuple may be: an EDC inception date and corresponding durationwhich taken together may specify the expiration date of an EDC. Tosupport complex rules that may be compound or variable or both, n-tuplesmay facilitate unlimited extensibility.

Additional EDC Field(s) 402 may include fields other than operandfields. For example, in some embodiments, Additional EDC Field(s) 402may include one or more “error detection” field(s)—such aschecksum(s)—to help detect corruption error(s) in a given EDC 115. Someerror detection field(s) may support correcting corruption error(s) inaddition to detecting them. Correction of corruption error(s) may alsobe facilitated by the symbology used to encode the EDC 115, for exampleQuick Response (QR) Code encoding may directly support corruption errorcorrection.

The Additional EDC Field(s) 402 may include field(s) including humanlanguage—for example in the form of text—which may be displayed on aprinted EDC 115 or otherwise displayed so that the shopper 110 or otherperson(s) may receive human language representation of the EDC 115. SuchEDC field(s) may specify representations such as: title(s),descriptions(s), requirement(s), restriction(s) and disclaimer(s).

The Additional EDC Field(s) 402 may include field(s) that facilitatetracking the distribution and shopper utilization of EDC(s). Forexample, a “source” field may specify the method of distribution of theEDC 115 to the shopper 110. Furthermore, a “requestor” field may includeshopper-identifying information such as a shopper's unique telephonenumber or a shopper's e-mail address. Additional EDC Field(s) 402 mayinclude one or more “sequence number” field(s) that may facilitateidentification(s) such as: identifying an EDC 115 distributed to one ormore shopper(s) 110, uniquely identifying a given EDC 115 distributed toa given shopper 110, and/or identifying a specific shopper or shoppersto whom an EDC may be distributed.

Returning to FIG. 2 and referring further to step 230. In someembodiments, an EDC authoring facility may be utilized to define a newEDC field(s) and correspondingly author EDC(s) with such newly definedEDC field(s), which may necessitate updating EDC Interpreter(s) 155 a tofacilitate processing such newly defined EDC field(s). Such updatespromptly disseminated may facilitate the seamless processing of EDC(s)115 that include newly defined EDC field(s).

Referring to step 240, a POS EDC Processing System 150 may optionally beupdated to utilize a revised version of the EDC Interpreter 155 a. TheEDC Interpreter 155 a may be updated via the WAN 160; updates mayinclude software and/or interpretable data—thereby realizing asignificant cost benefit over physical upgrades utilizing hardwareand/or firmware upgrades, and making updates less difficult.

Referring to FIG. 1 , a POS EDC Processing System 150 may receive EDC(s)115 which include newly defined EDC field(s) that the System 150 isunable to process. The POS Processor 155 may opt to query the EDCServer(s) 175 to determine if an updated version of the EDC Interpreter155 a may be available. If available, the POS Processor 155 may acquirea revised version of the EDC Interpreter 155 a from the EDC Server(s)175. the POS EDC Processing System 150 may be optionally updated at anytime. Updates to the POS EDC Processing System 150 may be initiated bythe System 150 (i.e., “pulled”). Updates to the POS EDC ProcessingSystem 150 may also be initiated remotely by the EDC Server 170 (i.e.,“pushed”). The EDC Server 175 may offer update(s) to EDC Interpreter(s)155 a.

Referring to step 250, EDC(s) 115 may be distributed physically—printedon paper and distributed via mass circulation platforms such as directmail, coupon books, magazines and newspapers, door hangers, and thebacks of grocery market receipts. Additionally, EDC(s) 115 may bedistributed electronically. For example, the image of a newly authoredEDC 115 may be emailed to numerous shoppers 110; or the Internetlocation of an EDC 115 posted on-line may be communicated via SMS textmessages or social media. EDCs 115 may be distributed by issuers,sellers, and a wide variety of third parties.

Referring to step 260, EDC(s) 115 presented at the POS by a shopper 110are processed by the POS EDC Processing System 150 utilizing the EDCInterpreter 155 a. FIG. 5 describes step 260 in greater detail bydepicting some embodiments of the POS processing of EDC(s) 115.

At step 520, the POS Input Device(s) 152 may be configured and utilizedto scan SKU(s) that identify purchase item(s) to the POS Processor 155.The POS Processor 155 may list such purchase item(s) in the ticket.Additionally, in some embodiments, shopper-identifying information maybe read by POS Input Device(s) 152 from one or more sources includingbut not limited to a loyalty card, a credit or debit payment card,personal information such as a driver license number, a shopper-providedphone number, or possibly utilizing biometrics. Furthermore, in someembodiments, an EDC 115 may include Additional EDC Field(s) 402 thatdirectly or indirectly identify the shopper 110. For example, an EDC 115may include a unique sequence number assigned and recorded prior to, orat, the time the EDC 115 was distributed specifically to the shopper110. The POS Processor 155 may record in the transaction log some or allshopper-identifying information—received at the POS and/or included inEDC(s) 115 presented by a given shopper 110—in association with theticket listing that shopper's scanned purchase item(s).

Referring to step 530, the EDC Interpreter 155 a parses an EDC 115presented by a shopper 110 and received from the POS Input Device(s)152. EDC(s) 115 may be presented by a shopper 110 in one of numerousforms, including but not limited to, wireless or printed. For example,an EDC may be presented in the form of a printed QR code.

FIG. 6 describes step 530 in greater detail by depicting someembodiments of parsing an EDC 115 presented at the POS by the shopper110. At step 640, the POS Processor 155 receives an EDC 115 from POSInput Device(s) 152.

At step 650, EDC error detection field(s) in the EDC Additional Fields402 may be utilized by an EDC Interpreter 155 a to validate that some orall of the field(s) included in an EDC 115 may be free of corruptionerrors. The EDC Interpreter 155 a may validate EDC field(s) included inan EDC 115 utilizing structure and syntax rules for EDCs known to theEDC Interpreter 155 a. The EDC Interpreter 155 a may validate EDCfield(s) included in an EDC 115 utilizing comparison against known-validfield values. A compound rule, for example may be validated byvalidating its component rules. A component rule, if specified by a ruleidentifier, can be validated simply by whether that identifier is knownto the EDC Interpreter 155 a. Similarly, numerous rules pre-analyzed andknown to the EDC Interpreter 155 a may be pre-cached so that a componentrule may be compared against the pre-cached rules to see if there is amatch. If a component rule is not known thusly to the EDC Interpreter155 a, the EDC Interpreter may optionally query the EDC Server(s) 170for an update that may make said component rule known to the EDCInterpreter 155 a. If said component rule is unknown to the EDCInterpreter 155 a, the corresponding compound rule may be deemed to beinvalid.

Referring to step 660—facilitated by error detection field(s) in the EDCAdditional Fields 402—the EDC Interpreter 155 a may detect and attemptto correct corruption errors in EDC field(s).

At Step 670, the EDC Interpreter 155 a checks if EDC field(s) may bedeemed to be erroneous. If EDC field(s) are deemed not to be erroneous,processing resumes at step 530 where the next received EDC 115—ifany—may be processed.

Referring to step 680, given that EDC field(s) are deemed to beerroneous, the EDC Interpreter 155 a rejects the erroneous EDC 115 andrecords the nature of the error(s) in the transaction log. The erroneousEDC 115 may be flagged accordingly to prevent further processing of thatEDC 115. In some embodiments, an ‘EDC error’ message may be displayedvia POS Display Device(s) 154. The next received EDC 115—if any—may beprocessed resuming at step 530.

Returning to FIG. 5 and referring to step 540, having parsed andsyntactically validated the EDC field(s) at step 540 above, the EDCInterpreter 155 a checks the semantics of the EDC 115 and authenticatesthe EDC as well.

FIG. 7 describes step 540 in greater detail by depicting someembodiments of semantically checking and authenticating an EDC 115.

Referring to step 720, the EDC Interpreter 155 a checks thequalification rule for semantic coherency. Given that each of the one ormore component rule(s) of the qualification rule is known to theInterpreter 155 a—as syntactically validated at step 530—the EDCInterpreter checks whether combination of said component rule(s) mayresult in inconsistency. For example, a qualification rule may becomposed of a static rule and a variable rule such that it specifies:‘quantity W of purchase item X—and—‘quantity [Y] of purchase itemX’—thus resulting in conflicting requirements for the quantity ofpurchase item X. Such inconsistency between component rules indicates tothe Interpreter 155 a that the qualification rule—which includes saidinconsistent component rules—may therefore be semantically incoherent.If the qualification rule is a simple rule it is deemed consistentwithout checking for consistency.

Referring further to step 720, the EDC Interpreter 155 a may apply“rule(s) of thumb” to check the sensibleness of the one or morecomponent rule(s) of the qualification rule. For example, in someembodiments, rule of thumb “maximum sensible” quantity values for eachpurchase item may be stored and utilized by the EDC Interpreter 155 a tocheck a component rule for sensibleness. For example, a qualificationrule may be composed of a variable rule that specifies ‘quantity [Z] ofpurchase item X’ where Z is specified by a corresponding operand fieldincluded in the Additional EDC Field(s) 402. The value of Z may bespecified as ‘6’ which may be sensible if purchase item X is cannedsoup, but may be nonsensible if the purchase item is a frozen turkey.Nonsensibleness in a component rule indicates to the Interpreter 155 athat the qualification rule is semantically incoherent.

Referring to step 730, the EDC Interpreter 155 a similarly semanticallychecks the redemption rule by checking its one or more component rule(s)for consistency and sensibleness. The EDC authoring facilities mayfacilitate authoring EDCs that are semantically coherent. An EDCdetermined to be semantically incoherent may be determined therefore tobe inauthentic.

Referring to step 740, the EDC Interpreter 155 a the EDC Interpreter 155a authenticate(s) the received EDC by combining the qualification ruleand the redemption rule as an “EDC rule set” and comparing said EDC ruleset against a list of known genuine rule sets. In some embodiments, theEDC rule set may be formed using a rule identifier—corresponding to thequalification rule and/or the redemption rule—instead of the rule(s). Sofor example an EDC rule set may have one or more of the following forms:‘qualification rule: redemption rule’; ‘qualification rule identifier:redemption rule’; ‘qualification rule: redemption rule identifier’; or‘qualification rule identifier: redemption rule identifier’.

Referring further to step 740, if the EDC rule set matches an entry inthe list of genuine rule sets, the EDC is determined to be authentic. Insome embodiments, if the EDC rule set does not match a genuine rule set,the EDC Interpreter may request an update including genuine rule setsfrom the EDC Server(s) 170. If the EDC rule set does not match an entryin the list of genuine rule sets, the EDC is not authentic.

Referring to step 750, the EDC Interpreter 155 a checks if the receivedEDC 115 is deemed authentic. If that EDC 115 is deemed authentic,processing resumes at step 550 where the next semantically validated EDC11—if any—may be processed.

Otherwise, at step 760, the EDC 115 may be rejected; the EDC 115 may beflagged as suspect; the presumed fraudulent EDC may be recorded in thetransaction log; and an exception message may be displayed on the POSDisplay Device(s) 154. The next semantically validated EDC 115—ifany—may be processed resuming at step 550.

Returning to FIG. 5 and referring to step 550, the EDC Interpreter 155 acompares the Received EDC(s) against the ticket and Redeems EDC(s) thatmatch.

FIG. 8 describes step 550 in greater detail. Referring to step 820, theEDC Interpreter 155 a compares the qualification rule set against theinformation recorded in the ticket—such as the listed purchase item(s)and corresponding quantity(s), and the POS transaction date.

Referring to step 830, the EDC Interpreter 155 a checks if thequalification rule may be deemed satisfied. If so, processing continuesat step 850.

Otherwise, referring to step 840, the unacceptable EDC is rejected; theEDC 115 is flagged as unacceptable; the EDC verification field setincluding the un-met condition(s) causing non-acceptance of the EDC 115may be recorded in the transaction log; and an exception message may bedisplayed on the POS Display Device(s) 154. The next received and parsedEDC 115—if any—may be processed resuming at step 550.

At step 850, the redemption rules of the accepted EDC 115 may be appliedto the ticket. Having accepted a given EDC 115 utilizing the POS EDCProcessing System 150, the seller (not shown) honors the EDC specifieddiscount out of seller's stock and/or proceeds and subsequently requestsreimbursement from the EDC issuer (not shown) or a reimbursing thirdparty based on accumulated EDC reimbursement totals stored in the EDCDepository 157. The next received and parsed EDC 115—if any—may beprocessed resuming at step 550.

Returning to FIG. 5 and referring to step 560, the EDC Interpreter 155 a“closes the transaction with SKU”; i.e., the EDC Interpreter 155 arecords in the transaction log the ticket information including thedetails of each of the listed purchase item(s), as well as EDC(s) 115verified against the ticket, as well as the final total discount. Insome embodiments, shopper-identifying information—if available—is alsologged. The logged transaction information may be subsequentlycommunicated to the EDC Server 170 to facilitate post-processing.

Referring again to FIG. 2 , at step 270, the POS Processor 155periodically communicates transaction log information to the EDC Server170 to facilitate post-processing. In post-processing, informationincluding transaction log information may be analyzed to determine whatseems to work successfully and what may be improved in a given EDCpromotion campaign—specific to an individual shopper 110 and/or toshoppers in aggregate. For example, various methods of distribution maybe compared to determine which have the highest EDC utilization rate. Insome embodiments, post-processing may include identifying an individualshopper's purchase inclinations and providing that shopper withadditional EDCs and other loyalty rewards, thus facilitating an ongoingloyaltizing cycle.

Many additions and modifications are possible. For example EDCs may be“personalizable”. In some embodiments, shopper(s) 110 may accessauthoring facilities to author non-fraudulent “mix-and-match” EDC(s)that may include issuer-acceptable shopper-selected options and may bedistributed to a given authoring shopper subject optionally to approvalby the issuer; and furthermore such “mix-and-match” EDC(s) may be fullyprocessed and accepted or rejected by POS EDC Processing System(s) 150.Optionally, such “mix-and-match” EDC(s) may be distributed to additionalshopper(s) 110.

As well, in some embodiments, shopper(s) 110 may author or otherwiseacquire non-fraudulent “bidding” EDC(s) that may include“bidding”-EDC-indicative encoding as well as “proposed” Discount Amount403/Discount Type 402 values and optionally other “proposed” EDC fieldvalues; and furthermore such “bidding” EDC(s) may be recognizable assuch and fully parsed, interpreted, validated, and accepted or rejectedby POS EDC Processing System(s) 150—based in part on corresponding“bid-matching” verification field set(s) discrete from the “bidding” EDC115 and accessed by EDC Interpreter 155 a from EDC depository(s)—EDCDepository 157, Remote EDC Depository 175, and/or third party EDCdepository.

Further pertaining to possible additions and modifications, EDC(s) maybe “customizable”. For example, in some embodiments, EDC issuers mayutilize EDC authoring facilities to customize EDCs by directly definingnew EDC fields. Furthermore, in some embodiments, Additional EDCField(s) 402 may include customized EDC verification field sets wherebythe issuer may define combinations of conventional and/or newlyconceived EDC verification field sets. For example, EDC verification maybe conditioned in part on: the shopper's identity, the day of the week,loyalty program membership, social network membership, and method ofpayment.

In some embodiments, a shopper 110 may utilize the POS EDC ProcessingSystem 150 to replace a misplaced or damaged EDC 115. For example, theink on a printed EDC 115 may be smudged so badly that an EDC 115 may beunreadable by POS Input Device(s) 152. In some embodiments, the shoppermay utilize POS Input Device(s) 152 to input shopper-identifyinginformation—such as that described previously above—so as to obtain fromthe EDC Depository 157 or optionally from the Remote EDC Depository 175the EDC 115 previously distributed specifically to that shopper 110. Insome embodiments, the shopper 110 may use POS Input Device(s) 152 andPOS Display Device(s) 154 to browse for and select the duplicate EDC 115from EDC(s) stored in the EDC Depository 157 or optionally from theRemote EDC Depository 175. In some embodiments, the shopper 110 may usean EDC Display Device 154—such as a printer—to reproduce EDC 115.

In some embodiments, POS Display Device(s) 154 may be optional or may beintegrated with POS Input Device(s). In some embodiments, a shopper'spersonal computing device—for example a “smart phone” may be utilized asa POS Input Device 152 and/or POS Display Device 154. In someembodiments, a shopper's personal computing device may be utilized as aPOS Processor 155 and/or shopper-specific EDC depository 157.

In some embodiments, a newly authored EDC may be described in a CouponDescription Language (CDL). CDL may describe a given EDC field using aset of one or more descriptors such as: Field Title, Field Type, FieldLocation, Field Size, Field Human Language Description, and Field Value.For example, the EDC field EDC Discount Type 402, may be described inCDL, optionally including but not limited to the following CDLdescriptors: Field Title=‘Discount Type Field’; Field Type=‘DiscountType’; Field Location=‘X bits offset’; Field Size=‘Y bits length’; FieldHuman Language Description=‘“Discount type—typically dollars orpercentage”’. Additionally, referring to the same example, CDL maydescribe the value of the given Discount Type 402 field utilizing theCDL descriptor Field Value=‘Discount Denominated in Z’.

In some embodiments, CDL may be used to encode some updates to EDCInterpreter(s) 155 a.

In some embodiments, CDL may be utilized as a common encoding utilizedfor communicating EDC(s) to and/or from third party servers.

In some embodiments, an EDC 115 may include EDC field(s) that includeCDL. In some embodiments, a given EDC 115 may include some or all of theCDL generated by EDC authoring facilities describing said EDC 115. SuchEDC(s) may be fully self-describing in CDL.

In some embodiments, the Additional EDC Fields 402 may encode a remoteaccess reference such as a universal resource identifier (URI) that maybe utilized to reference and access relatively large fields via WAN 160from Remote EDC Depository 175 or optionally from EDC Depository 157.So, for example, a 500 word “boiler plate” disclaimer might bereferenced indirectly by an EDC field rather than encoding that lengthyverbiage directly in the EDC 115.

In some embodiments, certain types of non-correctible errors detected ina given EDC may be compensated for or ignored. Such errors may be termed“non-critical errors”. For example, an error in an EDC field including ahuman language title may be a non-critical error. In contrast, somenon-correctible errors may ambiguate or prevent POS processing of agiven EDC 115. For example, such a “critical error” may be anon-correctible error in an EDC's EDC Coupon Type 401. In someembodiments, the EDC Interpreter 155 a may recognize non-criticalnon-correctible errors so as to ignore or compensate for them.

In some embodiments, error detection field(s) included in an EDC 115 maydetect errors due to imperfect forgery. An EDC Interpreter 155 a mightanalyze such errors and determine them to be the likely result of aforgery attempt. In this way, forgery attempts might not be misreportedin the transaction log as data corruption errors.

In some embodiments, encryption may be used to enhance the security ofan EDC 115 using strategies known to one versed in the arts includingtechniques such as watermarks and/or checksums.

In some embodiments, if a Received EDC is deemed inauthentic, a“potential fraud alert” may be communicated by the EDC Interpreter 155 ato the EDC Server(s) 170 including information such as the ticket, thesuspect EDC 115—and optionally—shopper-identifying information ifavailable.

In some embodiments, a POS EDC Processing System 150 may include morethan one EDC Processor 155—for example to facilitate fault toleranceand/or load balancing.

In some embodiments, a POS EDC Processing System 150 may include morethan one EDC Depository 157—for example to facilitate fault toleranceand/or load balancing.

In some embodiments, the EDC Depository 157 may be located remotely fromthe POS and accessed over a WAN 160 so as to allow POS EDC ProcessingSystems 150 at multiple seller facilities to share the same EDCDepository 157.

In some embodiments, the EDC Interpreter 155 a may be included in aprocessor other than the POS Processor 155 such that the EDC Interpreter155 a may be located remotely from the POS and accessed over a WAN 160so as to allow POS EDC Processing Systems 150 at multiple sellerfacilities to share the same EDC Interpreter 155 a.

In some embodiments, the Remote EDC Depository 175 may be fullydistributed and included in EDC Depositories 157 so as to facilitate a“virtual” Remote EDC Depository 175. In some embodiments utilizing sucha “virtual” Remote EDC Depository 175, the EDC Server(s) 170 may beoptional.

In some embodiments, EDC authoring facilities may store authored EDC(s)in and/or distribute authored EDC(s) to EDC Depository(s) 157.

Advantages of the above described embodiments include but are notlimited to: coupon fraud resistance; increased automation of couponprocessing; ease of shopper use; ease of issuing more varied andflexible coupon offers; ease of adding new EDC fields; ease of updatingEDC interpreters 155 a and coordinating said updates with additions ofnew EDC fields; ease of transitioning to and leveraging of newer andhigher density symbologies; ease of adapting to distributionmethods—including physical and electronic.

In summary, Enhanced Discrete Coupons may be used to incentivizepurchase of a nearly endless range of goods and services including “hardgoods” such as consumer electronics and groceries, “soft goods” such asextended product warranties, and services such as home carpet cleaning.The use of a flexible yet authenticable EDC—combined with systems andmethods that facilitate an adaptable POS Enhanced Discrete CouponProcessing System that may be updated for POS processing of new and/orrevised EDC features with relative ease and seamlessness—makes for ahighly adaptable system that may be extended, rather than superseded,for years to come.

1-23. (canceled)
 24. A method for processing an electronic data file, the method comprising: receiving, by a point of sale (POS) processor and from an external electronic data file server, an updated version of an interpreter module configured to process at least one internal rule of an electronic data file to the interpreter module; determining, by the updated version of the interpreter module, whether the electronic data file is semantically coherent; and upon determining, by the updated version of the interpreter module, that the electronic data file is semantically coherent, authenticating, by the updated version of the interpreter module, the electronic data file.
 25. The method of claim 24, further comprising: determining, by the updated version of the interpreter module, whether the electronic data file is corrupted based on one or more error detection fields; and upon determining, by the updated version of the interpreter module, that the electronic data file is corrupted, either i) correcting the electronic data file, or ii) logging and flagging a nature of the corruption in a transaction log to prevent further processing of the electronic data file.
 26. The method of claim 24, further comprising: upon determining, by the updated version of the interpreter module, that the electronic data file is semantically incoherent, logging the electronic data file as being inauthentic.
 27. The method of claim 26, wherein authenticating the electronic data file is based on comparing the at least one internal rule of the electronic data file against a set of genuine rules.
 28. The method of claim 24, further comprising: prior to receiving the electronic data file from a user device: scanning, by the POS processor, at least one purchase item; generating, by the POS processor, a ticket corresponding to the at least one purchase item; and upon authenticating the electronic data file: comparing, by the updated version of the interpreter module, the electronic data file against the ticket to determine if the electronic data file qualifies, and if the electronic data file qualifies, applying the electronic data file to the ticket.
 29. The method of claim 24, further comprising: querying, by the POS processor, the external electronic data file server for the updated version of the interpreter module that is configured to process the electronic data file rule unknown to the interpreter module.
 30. The method of claim 24, wherein determining, by the updated version of the interpreter module, whether the electronic data file is semantically coherent comprises: comparing a maximum sensible quantity for one of a plurality of purchase items to at least one electronic data file rule of the electronic data file rules encoded in the electronic data file, wherein the at least one electronic data file rule is a qualification rule specifying a quantity, if the specified quantity exceeds the maximum sensible quantity, identifying the electronic data file as semantically incoherent, and if the specified quantity does not exceed the maximum sensible quantity, identifying the electronic data file as semantically coherent.
 31. A system for processing an electronic data file, the system comprising: a point of sale (POS) device comprising one or more processors; and at least one data storage comprising instructions which, when executed by the one or more processors, cause the one or more processors to perform a method comprising: receiving, from an external electronic data file server, an updated version of an interpreter module configured to process at least one internal rule of an electronic data file to the interpreter module; determining, by invoking the updated version of the interpreter module, whether the electronic data file is semantically coherent; and upon determining, by invoking the updated version of the interpreter module, that the electronic data file is semantically coherent, authenticating, by invoking the updated version of the interpreter module, the electronic data file.
 32. The system of claim 31, further comprising: determining, by invoking the updated version of the interpreter module, whether the electronic data file is corrupted based on one or more error detection fields; and upon determining, by invoking the updated version of the interpreter module, that the electronic data file is corrupted, either i) correcting the electronic data file, or ii) logging and flagging a nature of the corruption in a transaction log to prevent further processing of the electronic data file.
 33. The system of claim 31, further comprising: upon determining, by invoking the updated version of the interpreter module, that the electronic data file is semantically incoherent, logging the electronic data file as being inauthentic.
 34. The system of claim 33, wherein authenticating the electronic data file is based on comparing the at least one internal rule of the electronic data file against a set of genuine rules.
 35. The system of claim 31, wherein the method further comprises: prior to receiving the electronic data file from a user device: scanning at least one purchase item; generating a ticket corresponding to the at least one purchase item; and upon authenticating the electronic data file: comparing, by invoking the updated version of the interpreter module, the electronic data file against the ticket to determine if the electronic data file qualifies, and if the electronic data file qualifies, applying the electronic data file to the ticket.
 36. The system of claim 31, wherein the method further comprises: querying the external electronic data file server for the updated version of the interpreter module that is configured to process the electronic data file rule unknown to the interpreter module.
 37. The system of claim 31, wherein determining whether the electronic data file is semantically coherent comprises: comparing a maximum sensible quantity for one of a plurality of purchase items to at least one electronic data file rule of the electronic data file rules encoded in the electronic data file, wherein the at least one electronic data file rule is a qualification rule specifying a quantity, if the specified quantity exceeds the maximum sensible quantity, identifying the electronic data file as semantically incoherent, and if the specified quantity does not exceed the maximum sensible quantity, identifying the electronic data file as semantically coherent.
 38. A non-transitory computer readable medium for processing an electronic data file, the non-transitory computer readable medium comprising instructions which, when executed by one or more processors of a point of sale (POS) device, cause the one or more processors to perform a method comprising: receiving, from an external electronic data file server, an updated version of an interpreter module configured to process at least one internal rule of an electronic data file to the interpreter module; determining, by invoking the updated version of the interpreter module, whether the electronic data file is semantically coherent; and upon determining, by invoking the updated version of the interpreter module, that the electronic data file is semantically coherent, authenticating, by invoking the updated version of the interpreter module, the electronic data file.
 39. The non-transitory computer readable medium of claim 38, further comprising: determining, by invoking the updated version of the interpreter module, whether the electronic data file is corrupted based on one or more error detection fields; and upon determining, by invoking the updated version of the interpreter module, that the electronic data file is corrupted, either i) correcting the electronic data file, or ii) logging and flagging a nature of the corruption in a transaction log to prevent further processing of the electronic data file.
 40. The non-transitory computer readable medium of claim 38, further comprising: upon determining, by invoking the updated version of the interpreter module, that the electronic data file is semantically incoherent, logging the electronic data file as being inauthentic.
 41. The non-transitory computer readable medium of claim 40, wherein authenticating the electronic data file is based on comparing the at least one internal rule of the electronic data file against a set of genuine rules.
 42. The non-transitory computer readable medium of claim 38, wherein the method further comprises: prior to receiving the electronic data file from a user device: scanning at least one purchase item; generating a ticket corresponding to the at least one purchase item; and upon authenticating the electronic data file: comparing, by invoking the updated version of the interpreter module, the electronic data file against the ticket to determine if the electronic data file qualifies, and if the electronic data file qualifies, applying the electronic data file to the ticket.
 43. The non-transitory computer readable medium of claim 38, wherein the method further comprises: querying the external electronic data file server for the updated version of the interpreter module that is configured to process the electronic data file rule unknown to the interpreter module. 